class UserRequest(BaseModel):
    message: str
    max_tokens: int = 1000
    temperature: float = 0.9
    system_msg: str = "You are an expert to answer"
    presence_penalty: float = 0
    frequency_penalty: float = 0
    persist_directory: str = "none"
    uid: int = 0
    llmtype: str="gpt-3.5-turbo"    


def classify_intent(msg):
    prompt = f"""Forget all your previous instructions. Your job is to classify intent.

    Choose one of the following intents:
    - the terminologies of fortune telling
    - telling about personal fortune
    - Consulting on personal plan 
    - Historical events
    - etc.
    Please don't make new intent except for the above examples.

    User: {msg}
    Intent:
    """
    messages=[ {"role": "user", "content": prompt}, ]
    try:
        response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages)
        return response.choices[0].message.content.strip()
    except:
        response = client.chat.completions.create(model="solar-1-mini-chat",
        messages=messages)
        return response.choices[0].message.content.strip()   


@app.post("/customerintention")
def chat_intention(req: UserRequest):
  context = req.dict()
  intent = classify_intent(req.message)
  if(any(keyword in req.message for keyword in keywordlist)):
      message = "사전 정의된 keyword, value set에서 답변을 가져옵니다."
  elif intent == "travel_plan":
      response = openai.ChatCompletion.create(model="gpt-3.5-turbo",    
      messages=[
          {"role": "system", "content": req.system_msg},
          {"role": "user", "content": req.message},
      ],
      temperature=req.temperature)
      message=response.choices[0].message.content
  elif intent == "customer_support":
      context["related_database"] = query_db(query=req.message, directory='cs_docx')
      message= rag1_chain.run(context)
  elif intent == "reservation":
      message="Here is reservation number: 0987654321"
  else:
      message = intent
  return { "answer": message }